code: def freeze(self):
      # Replace float weights by quantized weights
      self.weight = torch.nn.Parameter(
          QTensor.quantize(self.weight).to(self.weight.device)
      )
      bias_scale = self.in_scale * self.weight._scale
      self.bias = torch.nn.Parameter(
          QTensor.quantize(self.bias, torch.int32, bias_scale)
      )
  
file_path: quanto/test/nn/test_custom_qmodule.py
imports: import os
  from tempfile import TemporaryDirectory
  import pytest
  import torch
  from helpers import q_assert_close, random_qtensor
  from quanto import Calibration, QModuleMixin, QTensor, freeze, register_qmodule
label_desc: Use image node_id 3 for calling the QConv1D obj's underlying member method code with example usage: obj.freeze() without return types